In order to solve the problem that there are many factors affecting the operational effectiveness of carrier-based aircraft attacking land in complex battlefield situation, a operational effectiveness evaluation model of carrier-based aircraft attacking land based on BP neural network learning algorithm is proposed. Combined with the performance of carrier-based aircraft and battlefield environment, the evaluation index system of operational effectiveness of carrier-based aircraft attacking land was established by using analytic hierarchy process (AHP). The dynamic evaluation simulation is carried out by Matlab tool. The simulation results show that the model accuracy rate reaches 98.5%, and results also verify the validity and feasibility of the model, and can provide some decision-making information for the tactical application of carrier-based aircraft.